Harnessing The Power of Attention For Patch-Based Biomedical Image Classification

arXiv:2404.00949v1 Announce Type: new
Abstract: Biomedical image analysis can be facilitated by an innovative architecture rooted in self-attention mechanisms. The traditional convolutional neural network (CNN), characterized by fixed-sized windows, needs help capturing intricate spatial and temporal relations at the pixel level. The immutability of CNN filter weights post-training further restricts input fluctuations. Recognizing these limitations, we propose a new paradigm of attention-based models instead of convolutions. As an alternative to traditional CNNs, these models demonstrate robust modelling capabilities and the …

abstract analysis architecture arxiv attention attention mechanisms biomedical classification cnn convolutional neural network cs.cv filter image immutability network neural network pixel power relations self-attention spatial temporal training type windows